Research And Application Of Decision Tree Classification Algorithms

Classification is the important topic in the research field of data mining. There are many classification models such as decision tree, neural networks, genetic algorithms, rough sets, and so on. The thesis mainly research ID3 decision tree algorithm and its improved algorithm. First of all, the thesis introduced relative theories of decision tree, and compared several kinds of typical decision tree algorithms. Then a new algorithm based on attribute priority associate ID3(AID3) was proposed with advantages of ID3. The results of experiments proved that AID3 could raise the speed of constructing decision tree, at the same time, and overcame the ID3's shortcoming which was often partial to select some attributes with more value. Furthermore, the performance of classification of decision tree was also getting better and better with the enlarging of dataset scale. At last, the thesis discussed the application of AID3 algorithm to human resources management, the results had proved that AID3 algorithm was effective.